BioinformaticsBioinformaticsPeer-reviewed journal article
Zone Equalisation Normalisation For Improved Alignment of Epigenetic Signal
Tom WilsoniD, Thomas A. MilneiD, Simone G. RivaiD, Jim R. HughesiD
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Abstract
High-throughput genomic technologies have transformed our understanding of biological systems, but analysing these complex datasets remains challenging. Existing normalisation methods often struggle to accurately correct for technical variations across different experimental conditions, potentially leading to misleading biological interpretations. We introduce Zone Equalisation Normalisation (ZEN), a novel approach designed to improve signal normalisation across genomic datasets. By developing a flexible method that reduces technical noise whilst preserving biological signals, ZEN addresses critical limitations in current normalisation techniques. By applying ZEN to diverse genomic techniques, we reveal its robust performance in managing technical variations across different experimental platforms. ZEN provides researchers with a robust tool for more accurate and reliable genomic data analysis, potentially revealing biological insights that were previously obscured by technical variations.
- assay: whole-genome sequencing
- assay: ChIP-seq
- assay: ATAC-seq
- research focus: batch correction / integration
- research focus: variant calling
- research focus: dimensionality reduction
- approach: statistical model
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